因子分析和ELM在模拟电路故障诊断的应用

Application of factor analysis and ELM in analog circuit fault diagnosis

针对非线性模拟电路故障诊断中参数型故障元件定位的难题,提出采用因子分析优化的小波包能量谱和极限学习机的模拟电路故障诊断的方法。该方法首先对采集到的模拟故障数据进行小波包分解并提取不同频带的能量谱,然后利用因子分析对能量谱进行降维以提取故障特征,最后将提取的故障特征输入极限学习机进行故障诊断。仿真结果表明,该方法具有良好的区分能力,提高了故障诊断的效果。

Aiming at the problem of parametric fault diagnosis in nonlinear circuit, an approach utilizing wavelet bands. Then, the factor analysis algorithm is used to reduce the energy spectrum＇ s dimensionality. Finally, the fault features are inputted into extreme learning machine to identify different faults. The simulation results show that the proposed method can extract the fault signature effectively and get a good diagnosis result.